Flawed Integration Can Destroy Data Quality and Reliability

Email     |     Share  
1 | 2 | 3 | 4 | 5 | 6 | 7
Next Next

Accessibility and Consistency

As data volume, velocity, variability and variety increase, so do the stresses on today's software infrastructures when they can no longer make sense of data deluge. In a well-written, well-tuned application, over 90 percent of data access time is spent in middleware. And data connectivity middleware plays a critical role in how the application client, network and database resources are utilized. In any bulk load use case scenario, database connectivity is the cornerstone of performance. Over the years, technology vendors have made great strides in database optimization as well as the performance of processors and other hardware-based server components. As a result, the bottleneck migrated to the database middleware.

Analyzing large amounts of data across a multitude of business systems enables companies to optimize the performance of the sales team, identify patterns in the industry, or determine the efficacy of marketing. A variety of tools enable organizations to prepare the data, but if the quality is insufficient, it will provide unreliable insights.

Data connectivity and integration can be affected by a variety of factors including how it is entered, stored and managed. Maintaining high-quality data is reliant on regular updating, standardization and de-duplication. However, if these processes are flawed, the data can negatively sway organizational spend and productivity. When evaluating the quality of your organization’s data, a variety of characteristics need to be assessed.

In this slideshow, Paul Nashawaty, director of product marketing and strategy at Progress, looks at key factors organizations must consider to ensure their data remains of high quality.

 

Related Topics : Vulnerabilities and Patches, Resellers, Broadcom, Broadband Services, Supercomputing

 
More Slideshows

email12-190x128 Why Email Is a Business’ Greatest Untapped Resource

Five ways enterprises can use email analytics augmented by machine learning to surface insights that can help them ward off risk and meet or exceed goals across their organizations. ...  More >>

PorembaDigitalDisruption0x 9 Successful Digital Disruption Examples

Digital disruption isn't so much an IT project as the future of business, and this requires widespread collaboration across all units. ...  More >>

Media1-190x128.jpg 5 Ways to Boost Productivity with Content Automation

An effective content automation solution can ease the transition to a digital-first distribution strategy, helping companies preview and approve content across all platforms and media types. ...  More >>

Subscribe to our Newsletters

Sign up now and get the best business technology insights direct to your inbox.